The present invention relates generally to the field of seismic exploration and, more particularly, to methods for removal of unwanted energy from seismic data. Most particularly, it relates to the removal of coherent wave energy from seismic data acquired by geophones, hydrophones or other sensors.
In the oil and gas industry, seismic prospecting techniques are commonly used to aid in the search for and evaluation of subterranean hydrocarbon deposits. Typically, the goal of seismic prospecting is to construct a two dimensional (2-D) or three dimensional (3-D) representation of a subsurface lithologic formation in order to identify features that are indicative of hydrocarbon accumulations. Seismic prospecting generally consists of three separate stages: data acquisition, data processing and data interpretation. The success of a seismic prospecting operation depends on satisfactory completion of all three stages.
In the first stage of seismic prospecting, namely, seismic acquisition, a seismic source, such as, for example, dynamite, is used to generate a downgoing seismic wavefield or signal that propagates into the earth and is partially reflected by subsurface seismic reflectors (i.e., interfaces between subsurface lithologic or fluid units having different elastic properties). The reflected or upgoing wavefield or signals (known as “seismic reflections”) are detected by seismic receivers located at or near the surface of the earth, at or near the water surface, or at or near the seafloor. The detected signals are converted into electric signals and recorded, thereby generating a seismic survey of the subsurface. The recorded signals, or seismic energy data, can then be processed to yield information relating to the lithologic subsurface formations identifying such features, as, for example, lithologic subsurface formation boundaries. The seismic energy recorded by each seismic receiver for each source activation during the data acquisition stage is known as a “trace.”
The seismic receivers utilized in such operations typically include pressure sensors, such as hydrophones, and velocity sensors, such as single or multi-component geophones. Utilizing a dual sensor configuration, namely, the combination of a geophone and a hydrophone, various summation techniques of the two types of wavefield recordings can be utilized to improve the accuracy of a trace.
With respect to the propagating wavefield, the two main ways in which seismic energy typically travels through the earth are either as compressional waves, commonly referred to as “P-waves”, or as shear waves, commonly referred to as “S-waves”. P-waves are body waves in which particle motion is in the direction of propagation. S-waves are body waves in which particle motion is perpendicular to the direction of propagation The term “body wave” refers to the fact that P- and S- waves can exist within a medium as well as at the boundary between media or lithologic units, in contrast to “boundary waves” that can exist only at a boundary. Both body waves and boundary waves consist of coherent energy. Coherent energy is energy that follows a particular path either within the subsurface or along the boundary between media or lithologic formations. Random or chaotic propagation is generally referred to as non-coherent noise. Coherent energy manifests itself as following a particular pattern, such as, for example, linear or hyperbolic patterns, across different types of data collections (sorts), e.g. shot, receiver or common depth point (CDP) sorts. Converted waves are a type of coherent energy that travels first as one type of wave, e.g. P-wave, and then as another, e.g. S-wave, the conversion between wave types occurring at the seismic reflectors. The most prevalent type of converted waves used in seismic exploration are “PS-waves” representing waves that are down-going into the earth as P waves and are reflected to the surface of the earth as S-waves. Another converted wave path for marine data would be the PSP-wave path where the wave travels into the earth as a P-wave and is reflected upward at some depth within the earth as an S-wave. This S-wave is then converted to a P-wave at the sea floor and is recorded as a P-wave by hydrophones near or at the water surface. It is well known that geophones can detect both P- and S-waves, while hydrophones are capable of only detecting P-waves. In part because of this, geophone data is historically “nosier” than hydrophone data. More specifically, geophone data can be contaminated with both S-waves and P-waves, while hydrophone data can only sample P-waves. For coherent energy noise removal, it is necessary to consider both P-wave and S-wave data detected by the sensors as energy from both types of detectors can be coherent.
Once the seismic data has been acquired, it is then processed during the second stage of seismic prospecting in part to remove unwanted energy. For example, in dual sensor acquisition, wave energy recorded by the hydrophones and by the geophones can be combined to minimize the effect of the reflection of energy by the water surface, often referred to as ghosts. Seismic processing typically involves the use of various mathematical algorithms that are applied to the data to enhance its signal content and to make it more amenable to interpretation. One of the main objectives of the data processing stage is to remove or at least attenuate unwanted recorded energy that contaminates the primary seismic signal. This unwanted energy is typically referred to as “noise”, and represents such things as, for example, multiple energy, i.e. energy that has reflected more than once from a reflector, electrical interference, noise caused by cultural factors such as oil drilling rigs, wind noise, etc.
Techniques for noise removal such as common-midpoint (CMP) or common depth point (CDP) stacking (the term CDP will be used in this application for the collection of traces obtained at one surface location), deconvolution, frequency filtering, multiple attenuation, and pre-stack and post-stack migration, etc., are well known in the industry. Generally the traces common to a surface location will have common characteristics that can be capitalized upon in order to remove noise. These traces will generally have the averages of the x and y coordinates of the shot and receiver in common or very close. Through such processing techniques, the strength of the primary signal energy represented in a trace can be enhanced, while the strength of the unwanted noise energy can be weakened, thus increasing the signal-to-noise, or S/N, ratio. Among the noise energy that can be removed with these procedures is coherent wave noise energy. In this regard, it is generally desirable to suppress coherent wave noise energy in favor of the pure-mode P-wave primary energy. The term “P-wave primary energy” is used to differentiate between primary and multiple energy, i.e. energy that has bounced back from the reflector once (primary) as opposed to energy that has taken more than one path in the subsurface (multiple), to differentiate between P- and S-waves and to differentiate between true reflectors and other types of signals such as linear noise trains.
Various attempts have been made in the prior art to remove coherent wave noise energy from a P-wave primary seismic signal. For example, the velocity difference between the P-wave primary signal energy and the coherent wave noise energy can be utilized for such processing. Generally the velocity of the coherent wave noise energy will be less or of a different type, e.g. hyperbolic versus linear, than the velocity of the P-wave primary energy. For hyperbolic moveout a velocity can be chosen for normal moveout (NMO) correction, i.e. time corrections that change the time position of energy from a reflector as a function of offset, shot to receiver distance. When the velocity to a particular reflector is correct, the energy from that reflector after NMO, appears at a constant time in a data sort that spans several offsets. Typically, for example, it is desirable to select the correct velocity so that P-wave primary energy reflectors appear at a constant time in a data sort, i.e., the P-wave primary energy is flat. However, a velocity can be chosen such that the P-wave primary energy is overcorrected, i.e. curves upward, and the coherent wave noise signal is undercorrected, i.e. curves downward. CDP, shot and receiver sorts, for example, all have a range of offsets and would exhibit this behavior. If the velocity for NMO is too slow for a reflector, the reflector after NMO in one of these sorts will curve upward. If the velocity is too fast the reflector will curve downward. For geophones, some coherent wave noise energy is organized in the receiver domain but unorganized in the shot or CDP domain. For example, the sensing of S-waves by geophones depends on the orientation of the geophone with respect to the upcoming wave, i.e. the angle of the geophone with the material underlying the geophone. This will be geophone (receiver) consistent but not shot or CDP consistent. Hence by sorting the seismic data into a receiver sort, i.e. all the traces going into a particular receiver, and NMO correcting with a velocity between the P-wave data and converted wave data, the P-wave primary data will be overcorrected and the converted wave data will be under corrected. A decomposition technique such as frequency-wavenumber (F-K) filtering or tau-p (Radon) filtering can then be used to separate the undercorrected and overcorrected energy. For example, utilizing tau-p filtering, undercorrected energy, i.e. energy curving downward in a NMO corrected receiver gather, will map to the positive moveout section of the Radon space. Overcorrected energy, i.e. energy curving upward, will map to the negative moveout portion of the Radon space. Whichever filtering technique is used, the procedure transforms the NMO corrected data into a transform space where the undercorrected and overcorrected energy separate. Then the portion of the transform plane corresponding to undesirable data is strongly reduced in magnitude, i.e. filtered out. The remaining data is transformed back into X-T space. This is the method discussed in U.S. Pat. No. 6,738,715.
Other patents pertaining to this area of seismic data processing are as follows. U.S. Pat. No. 5,191,526 teaches FK filtering to separate signal and noise and uses wavenumbers, decay constants, amplitudes and phases to discriminate between P-wave primary data and coherent noise. In another embodiment in this patent, the noise areas of the FK plane are summed together and subtracted from the input data. U.S. Pat. No. 5,067,112 teaches frequency-distance, FX, filtering to determine the frequencies at which coherent noise resides, wherein wavenumbers corresponding to such frequencies are removed by filtering. U.S. Pat. No. 4,380,059 pertains more to multiple removal but uses an FK inverse filter to remove portions of the FK plane pertaining to multiples.